Enhanced frilled lizard optimization (EFLO) algorithm for optimizing decision variables in electric vehicle charging station placement K. P. Ranjusha, B. Amutha Artificial Intelligence Powered Electrical Machine Design Optimization Control and Innovation, 2026 The Enhanced Frilled Lizard Optimization (EFLO) algorithm is an innovative approach designed to improve optimization solutions for complex problems, including the placement of electric vehicle (EV) charging stations. This paper presents a detailed study of the EFLO, highlighting its improvements over the traditional Frilled Lizard Optimization (FLO) algorithm. EFLO addresses the challenges posed by random sampling and local optima by incorporating a fitness-aided random integer. The paper explores the algorithm’s effectiveness in optimizing multiple objectives, including the number and location of fast and slow charging points. Experiments conducted in various real-world scenarios demonstrate the superiority of EFLO over existing optimization techniques, offering better solutions for EV infrastructure deployment.
Edge Computing for Energy-Efficient Internet of Things: Concepts, Technologies, and Applications Delsi Robinsha S, B. Amutha Innovation and Sustainability in Electric and Autonomous Mobility, 2025 In today's world, the utilization ratio of IoT devices has been increased in the production of massive data, and these gigantic problems were posed in energy consumption and environmental conservation. To address with these problems, there is an innovative concept known as the edge computing that means computation is carried closer to the place where the data is collected. This is done in view of the above stated challenges and difficulties. Building the concept of ‘Efficient Edge For Sustainable IoT' As a response to the presented research questions, this chapter employs the energy-efficient edge computing architecture concept to explore the Efficient Edge as a sustainability strategy for the IoT. It elaborates crucial questions related to edge computing and reveals the position of this concept for minimizing the energy consumption, enhancing resource efficiency, as well as the rational data processing on the end side of the network. Some of the diverse technologies and strategies expounded in this chapter to achieve energy efficiency in edge computing include energy-aware task offloading, load balancing as well as the integration of renewable energy. Besides this, it looks at the joy of optimization and solutions on battery-powered Internet of Things devices and issues on scalability for edge computing. In this chapter, the focus is made on how the Efficient Edge allows IoT ecosystems to be sustainable, scalable, and resilient, while the use of real-world case studies and the analysis of the future looks like.
Smart mobility: Cognitive computing in modern transportation systems S. Delsi Robinsha, B. Amutha, D. Vanusha, D. Vathana Cognitive Computing for Smart Automotive Transportation Technology and Applications, 2025 The incorporation of cognitive computing into contemporary transportation systems represents a significant step forward in the quest for smart mobility. This integration improves the effectiveness, safety, and sustainability of urban and interurban transportation networks. The purpose of this chapter is to investigate the transformative role that cognitive computing technologies, which include artificial intelligence (AI), machine learning (ML), and the Internet of Things (IoT), play in revolutionising transportation infrastructures. Cognitive computing makes it possible to construct intelligent transportation networks that are capable of self-optimisation and dynamic decision-making. This is accomplished through the utilisation of real-time data analytics, predictive modelling, and adaptive systems. Some of the most important uses of these technologies are driverless vehicles, enhanced traffic management systems, predictive maintenance, and personalised travel experiences. These applications highlight the massive influence that these technologies have. The study also discusses the difficulties that are linked with data privacy, cybersecurity, and ethical issues, all of which are essential for the implementation of cognitive technologies in a responsible manner. In the end, cognitive computing is essential for the achievement of smart mobility because it provides novel answers to the difficulties that are now being faced in the transportation industry and paves the way for the evolution of sustainable urban development.
Bridging the gap: Innovations in ITS for rural mobility challenges S. Delsi Robinsha, B. Amutha Urban Mobility and Challenges of Intelligent Transportation Systems, 2025 In rural areas, access to technology is constrained, there is a low population density, and there is little infrastructure. These are all issues that are particular to rural locations. Inadequate mobility alternatives are frequently the result of these issues, which lowers the quality of life and economic prospects available to people living in rural areas. This chapter investigates the revolutionary potential of information technology systems (ITS) in terms of bettering rural transport and addressing the concerns that have been raised. Infrastructure Technology (ITS) has the potential to greatly improve the efficiency, dependability, and safety of rural transportation networks by utilising smart transit systems, adaptive traffic management, and better safety measures.
Leveraging intelligent transportation systems for predictive roadway maintenance S. Delsi Robinsha, B. Amutha, D. Vanusha, R. Prithviraj Urban Mobility and Challenges of Intelligent Transportation Systems, 2025 Intelligent Transportation Systems (ITS) are a significant development in contemporary infrastructure that have the potential to revolutionise the maintenance of roadways through the application of predictive analytics. In order to improve the safety, efficiency, and durability of road networks, this chapter investigates the possibility of integrating intelligent transportation systems (ITS) with predictive maintenance tactics. Through the utilisation of real-time data collecting, advanced sensor technologies, and machine learning algorithms, Intelligent Transportation Systems (ITS) are able to recognise patterns and forecast the deterioration of roadways before it becomes critically important. This proactive strategy makes it possible to make timely interventions, which in turn reduces the frequency of emergency repairs and the cost of such repairs, minimises disturbances to traffic, and improves the overall experience of travellers on roads. Several components of Intelligent Transportation Systems (ITS) are discussed in this chapter.
Channel estimation and secure data transmission using hybrid particle swarm optimisation–gray wolf optimisation-leaky least-Mean-Square and affine elliptic curves cryptography algorithm in MU-multi-input multi-output orthogonal frequency division multiplexing system Jeya R, B. Amutha International Journal of Communication Systems, 2025 Summary In a huge multi‐input multi‐output orthogonal frequency divisions multiplexing (MIMO‐OFDM), an exact Channel State Information (CSI) is required to understand the system performance, which includes high spectrum together with energy efficiency. Using the OFDM, substantial numbers of pilots are distributed over a huge range of time–frequency sources to efficiently assess a vast range of channel coefficients in space along with the frequency domains, forfeiting spectral efficiency. Here, an optimised Channel Estimation (CE) framework aimed at the MU‐MIMO OFDM system is proposed utilising Hybrid Particle Swarm Optimisation–Gray Wolf Optimisation‐Leaky Least‐Mean‐Square (HPG‐LLMS) to attain high accurateness and secure data transmission (DT) with the aid of proposed Affine ECC. Herein, the video is considered as an input in the transmitter side and transformed into data frames and compressed with the help of ASCII‐based Huffman algorithm. Using Affine ECC, the compressed data are encrypted as well as modulated with the help of the MQPSK method. Then, transmute the modulated data into IFFT and incorporate the Guard Interval (GI) to the data. And then, over the Multi‐Path Channel (MPC), the symbols will be passed on to the receiver with the Additives White Gaussian Noise (AWGN). Execute the Inverse operations on the receiver side and centred on fuzzy centred priority scheduling algorithm (FPSA), sent the data to the user. Lastly, utilising HPG‐LLMS, the CE is performed.
Electric Vehicles: A Mini Overview Ranjusha Kp, B. Amutha Proceedings 2024 Recent Advances in Sustainable Engineering and Future Technologies Raseft 2024, 2024
Advanced Cognitive Models and Algorithms J. Ramkumar, M. Baskar, B. Amutha Cognitive Engineering for Next Generation Computing A Practical Analytical Approach, 2021
Website reputation system B. Amutha, Prabhav Gupta, Himanshu Kumar, C Castillo, D Donato, et al. International Journal of Innovative Technology and Exploring Engineering, 2019
Performance on security problem and challenge in wireless sensor network International Journal of Innovative Technology and Exploring Engineering, 2019
Performance analysis and comparison of different modulation schemes with channel estimation methods for MIMO-OFDM system International Journal of Innovative Technology and Exploring Engineering, 2019
Study of Service Chain Optimization in Cloud Environment Prathamesh Purohit, Ruturaj Kadikar, M. Susila, B. Amutha Proceedings of the 2018 IEEE International Conference on Communication and Signal Processing Iccsp 2018, 2018
An obstacle avoidance algorithm with spatial and temporal constraints for visually impaired International Journal of Applied Engineering Research, 2015
Design and implementation of layered security protocol using customized chaotic code transformation for military applications International Journal of Applied Engineering Research, 2015
Retraction Note: A Machine Learning Based Detection and Mitigation of the DDOS Attack by Using SDN Controller Framework M Revathi, VV Ramalingam, B Amutha Wireless Personal Communications, 1-1 , 2026 2026
Empowering Healthcare: Harnessing the Potential of the Medical Internet of Things for Advanced Patient Care S Delsi Robinsha, B Amutha Advancing Healthcare with the Medical Internet of Things: Revolutionizing … , 2026 2026
Empowering Healthcare: Harnessing SD Robinsha, B Amutha Advancing Healthcare with the Medical Internet of Things: Revolutionizing … , 2026 2026
Sustainable development of E-mobility in urban areas using knowledge-based artificial network (KANM), behavioral learning theory (BLT) and distributed optimization algorithm (DOA) KP Ranjusha, B Amutha International Journal of Information Technology, 1-11 , 2026 2026 Citations: 1
Enhancing diagnostic accuracy: the role of explainable artificial intelligence in clinical decision support SD Robinsha, B Amutha, D Vanusha, D Vathana, U Sugandh Explainable AI in Clinical Practice, 255-269 , 2026 2026
Edge Computing for Energy-Efficient Internet of Things: Concepts, Technologies, and Applications B Amutha Innovation and Sustainability in Electric and Autonomous Mobility, 209-230 , 2026 2026
An IoT-Enabled Health Monitoring and Emergency Hospital Navigation System Using Disease Classification and Predictive Modelling SD Robinsha, B Amutha, D Vanusha, AD Rege 2025 2nd International Conference on Computing and Data Science (ICCDS), 1-7 , 2025 2025 Citations: 1
Smart Mobility: Cognitive Computing in Modern Transportation Systems SD Robinsha, B Amutha, D Vanusha, D Vathana Cognitive Computing for Smart Automotive Transportation, 35-52 , 2025 2025
Spark Booster-An Optimized IoT Architecture for Energy Sector Delving Predictive Analysis on Energy Usage with Stochastic Monte Carlo Method SD Robinsha, B Amutha, V Ponnusamy IEEE Access , 2025 2025 Citations: 2
A Simple Moving Average-Based Predictive IoT Architecture for Energy Consumption in Smart Cities B Amutha 2025 International Conference on Computing and Communication Technologies … , 2025 2025 Citations: 2
Interfacing multi-modal AI with IoT: Unlocking new frontiers S Delsi Robinsha, B Amutha Multimodal Generative AI, 323-346 , 2025 2025 Citations: 4
An Approach to System Design for Enabling Device Interoperability in Internet of Things-Enabled Intelligent Transportation Systems for Smart Cities S Delsi Robinsha, B Amutha Internet of Vehicles and Computer Vision Solutions for Smart City … , 2025 2025 Citations: 4
Transportation networks that leverage internet of things architectures: A review SD Robinsha, B Amutha AIP Conference Proceedings 3162 (1), 020114 , 2025 2025 Citations: 5
Leveraging Intelligent Transportation Systems for Predictive Roadway Maintenance SD Robinsha, B Amutha, D Vanusha, R Prithviraj Urban Mobility and Challenges of Intelligent Transportation Systems, 489-506 , 2025 2025 Citations: 1
Bridging the Gap: Innovations in ITS for Rural Mobility Challenges SD Robinsha, B Amutha Urban Mobility and Challenges of Intelligent Transportation Systems, 147-168 , 2025 2025 Citations: 1
Comparative Analysis of Several Different Multimodal Methods for the Development of Generative Artificial Intelligence M Saranya, B Amutha Generative Artificial Intelligence and Ethics: Standards, Guidelines, and … , 2025 2025
A Comparative Study on the Evaluation of ChatGPT and BERT in the Development of Text Classification Systems M Saranya, B Amutha Generative Artificial Intelligence and Ethics: Standards, Guidelines, and … , 2025 2025 Citations: 2
Electric Vehicles: A Mini Overview R Kp, B Amutha 2024 Recent Advances in Sustainable Engineering and Future Technologies … , 2024 2024
CyberDefender: an integrated intelligent defense framework for digital-twin-based industrial cyber-physical systems S Krishnaveni, TM Chen, M Sathiyanarayanan, B Amutha Cluster Computing 27 (6), 7273-7306 , 2024 2024 Citations: 53
Two party key exchange protocol based on duo circulant matrices for the IoT environment B Amutha, R Perumal International Journal of Information Technology 16 (6), 3585-3596 , 2024 2024 Citations: 7
MOST CITED SCHOLAR PUBLICATIONS
A machine learning based detection and mitigation of the DDOS attack by using SDN controller framework M Revathi, VV Ramalingam, B Amutha Wireless Personal Communications 127 (3), 2417-2441 , 2022 2022 Citations: 84
Region centric minutiae propagation measure orient forgery detection with finger print analysis in health care systems M Baskar, R Renuka Devi, J Ramkumar, P Kalyanasundaram, ... Neural Processing Letters 55 (1), 19-31 , 2023 2023 Citations: 81
Retracted Article: Invariant packet feature with network conditions for efficient low rate attack detection in multimedia networks for improved QoS M Suchithra, M Baskar, J Ramkumar, P Kalyanasundaram, B Amutha Journal of ambient intelligence and humanized computing 12 (5), 5471-5477 , 2021 2021 Citations: 79
WITHDRAWN: ResNet-deep neural network architecture for leaf disease classification K Deeba, B Amutha Microprocessors and Microsystems, 103364 , 2020 2020 Citations: 78
Location update accuracy in human tracking system using zigbee modules B Amutha, M Ponnavaikko arXiv preprint arXiv:0912.1019 , 2009 2009 Citations: 78
CyberDefender: an integrated intelligent defense framework for digital-twin-based industrial cyber-physical systems S Krishnaveni, TM Chen, M Sathiyanarayanan, B Amutha Cluster Computing 27 (6), 7273-7306 , 2024 2024 Citations: 53
Optimized semiblind sparse channel estimation algorithm for MU-MIMO OFDM system R Jeya, B Amutha Computer Communications 146, 103-109 , 2019 2019 Citations: 40
A novel software‐defined networking approach for load balancing in data center networks VD Chakravarthy, B Amutha International journal of communication systems 35 (2), e4213 , 2022 2022 Citations: 33
Public key exchange protocols based on tropical lower circulant and anti circulant matrices B Amutha, R Perumal AIMS math 8 (7), 17307-17334 , 2023 2023 Citations: 29
An efficient botnet detection with the enhanced support vector neural network S Jagadeesan, B Amutha Measurement 176, 109140 , 2021 2021 Citations: 28
Path based load balancing for data center networks using SDN VD Chakravarthy, B Amutha International Journal of Electrical and Computer Engineering (IJECE) 9 (4 … , 2019 2019 Citations: 24
Blockchain and extreme learning machine based spectrum management in cognitive radio networks C Rajesh Babu, B Amutha Transactions on Emerging Telecommunications Technologies 33 (10), e4174 , 2022 2022 Citations: 23
Classification algorithms of data mining K Deeba, B Amutha Indian Journal of Science and Technology 9 (39) , 2016 2016 Citations: 21
Development of a ZigBee based virtual eye for visually impaired persons B Amutha, K Nanmaran 2014 International Conference on Indoor Positioning and Indoor Navigation … , 2014 2014 Citations: 20
Energy efficient hidden Markov model based target tracking mechanism in wireless sensor networks B Amutha, M Ponnavaikko Journal of Computer Science 5 (12), 1082 , 2009 2009 Citations: 13
Velocious: A resilient IoT architecture for 6G based intelligent transportation system with expeditious movement mechanism SD Robinsha, B Amutha Wireless Personal Communications, 1-22 , 2024 2024 Citations: 12
A hybrid method for improving GPS accuracy for land vehicle navigation system K Venkatraman, B Amutha, SR Sankar INTERACT-2010, 74-79 , 2010 2010 Citations: 12
A novel energy-efficient data aggregation protocol for cognitive radio based wireless multimedia networks CR Babu, B Amutha Peer-to-Peer Networking and Applications 14 (4), 2452-2461 , 2021 2021 Citations: 11
Software-defined network assisted packet scheduling method for load balancing in mobile user concentrated cloud VD Chakravarthy, B Amutha Computer Communications 150, 144-149 , 2020 2020 Citations: 11
Analysis of efficient unmanned aerial vehicles to handle medical emergency data transmission surveillance system by using wireless body area network B Manickavasagam, B Amutha Computer Communications 152, 19-33 , 2020 2020 Citations: 10
